Abusive Span Detection for Vietnamese Narrative Texts
Authors: 
Nhu-Thanh Nguyen, Khoa Thi-Kim Phan, Duc-Vu Nguyen, Ngan Luu-Thuy NguyenAuthors Info & Claims
Nhu-Thanh Nguyen, Khoa Thi-Kim Phan, Duc-Vu Nguyen, Ngan Luu-Thuy NguyenAuthors Info & ClaimsPages 471 - 478
Abstract
Abuse in its various forms, including physical, psychological, verbal, sexual, financial, and cultural, has a negative impact on mental health. However, there are limited studies on applying natural language processing (NLP) in this field in Vietnam. Therefore, we aim to contribute by building a human-annotated Vietnamese dataset for detecting abusive content in Vietnamese narrative texts. We sourced these texts from VnExpress, Vietnam’s popular online newspaper, where readers often share stories containing abusive content. Identifying and categorizing abusive spans in these texts posed significant challenges during dataset creation, but it also motivated our research. We experimented with lightweight baseline models by freezing PhoBERT and XLM-RoBERTa and using their hidden states in a BiLSTM to assess the complexity of the dataset. According to our experimental results, PhoBERT outperforms other models in both labeled and unlabeled abusive span detection tasks. These results indicate that it has the potential for future improvements.
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December 2023
1058 pages
ISBN:9798400708916
DOI:10.1145/3628797
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Published: 07 December 2023
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SOICT 2023
SOICT 2023: The 12th International Symposium on Information and Communication Technology
December 7 - 8, 2023
Ho Chi Minh, Vietnam
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